Advancing the Science and Practice of Ecological Momentary Assessment

推进生态瞬时评价的科学性与实践性 项目总结 本提案是对PAR-16-260《方法学与测量》项目公告的回应 社会科学和行为科学“的具体目标是改进实时数据捕获中的测量 经历。生态瞬时评估(EMA)是一系列重复捕获自我报告的技术 当人们开始他们的日常生活时，这对评估主观状态特别有用。它的目标是实现 对症状、幸福感、情感、信念以及社会和物理环境进行精确和细粒度的测量 在自然环境中随着时间的推移。尽管EMA方法被广泛应用于行为、社会和医学研究，但 是我们理解中的关键差距，必须加以解决，才能以最佳方式理解和应用EMA方法。 该提案审查了五个问题，以提供有关EMA和实用工具的必要概念信息 进行严格、高质量和可复制的EMA研究；它采用了几种新的方法来实现这些 目标。要调查的主要问题包括：了解受访者如何解释和即时回答 通过进行实时、定性的访谈来回答问题；确定各种EMA协议因素(例如 评估、评估天数)影响受访者的选择偏差并影响瞬时遵从性， 以及开发有效评估特定设计的影响的工具；测试新的 使用现代心理测量学原理(项目反应理论)生成EMA测量工具，并进行评估 EMA计算机化适应性测试的可能性；检查EMA的一个核心特征-EMA报告较少 比召回报告更有偏见--将这两类自我报告与客观标准进行比较；最后， 试验性地检查了被假设为对EMA报告产生偏差的因素，基于以下想法 自我监测和报告可能会影响报告的性质(即测量反应性)。

Advancing the Science and Practice of Ecological Momentary Assessment PROJECT SUMMARY This proposal is submitted in response to the program announcement PAR-16-260, “Methodology and Measurement in the Social and Behavioral Sciences,” with the specific goal of improving measurement in real-time data capture of experiences. Ecological Momentary Assessment (EMA) is a family of techniques for repeatedly capturing self-reports while people go about their everyday lives, and is particularly useful for assessing subjective states. It aims to achieve accurate and granular measurement of symptoms, well-being, affect, beliefs, and the social and physical environment over time in natural contexts. Although EMA methods are widely used in behavioral, social, and medical research, there are critical gaps in our understanding that must be resolved for EMA methods to be optimally understood and applied. This proposal examines five issues to provide necessary conceptual information about EMA and practical tools for conducting rigorous, high-quality, and replicable EMA studies; it employs several novel approaches for achieving these goals. The main issues to be investigated include: understanding how respondents interpret and answer momentary questions by conducting real-time, qualitative interviews; determining how various EMA protocol factors (e.g., length of assessment, number of days of assessments) impact selection bias of respondents and influence momentary compliance, and the development of a tool for efficiently evaluating the impact of particular designs; testing a model for a new generation of EMA measurement tools using modern psychometric principles (Item Response Theory), and evaluating the possibility of computerized adaptive tests for EMA; examining a core feature of EMA – that EMA reports are less biased than recall reports – by comparing both types of self-reports with an objective standard; and, finally, experimentally examining factors that have been hypothesized to bias EMA reporting, based on the idea that the act of self-monitoring and reporting may influence the nature of reports (i.e., measurement reactivity).